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Ghaffar SA, Tahir H, Muhammad S, Shahid M, Naqqash T, Faisal M, Albekairi TH, Alshammari A, Albekairi NA, Manzoor I. Designing of a multi-epitopes based vaccine against Haemophilius parainfluenzae and its validation through integrated computational approaches. Front Immunol 2024; 15:1380732. [PMID: 38690283 PMCID: PMC11058264 DOI: 10.3389/fimmu.2024.1380732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 04/01/2024] [Indexed: 05/02/2024] Open
Abstract
Haemophilus parainfluenzae is a Gram-negative opportunist pathogen within the mucus of the nose and mouth without significant symptoms and has an ability to cause various infections ranging from ear, eye, and sinus to pneumonia. A concerning development is the increasing resistance of H. parainfluenzae to beta-lactam antibiotics, with the potential to cause dental infections or abscesses. The principal objective of this investigation is to utilize bioinformatics and immuno-informatic methodologies in the development of a candidate multi-epitope Vaccine. The investigation focuses on identifying potential epitopes for both B cells (B lymphocytes) and T cells (helper T lymphocytes and cytotoxic T lymphocytes) based on high non-toxic and non-allergenic characteristics. The selection process involves identifying human leukocyte antigen alleles demonstrating strong associations with recognized antigenic and overlapping epitopes. Notably, the chosen alleles aim to provide coverage for 90% of the global population. Multi-epitope constructs were designed by using suitable linker sequences. To enhance the immunological potential, an adjuvant sequence was incorporated using the EAAAK linker. The final vaccine construct, comprising 344 amino acids, was achieved after the addition of adjuvants and linkers. This multi-epitope Vaccine demonstrates notable antigenicity and possesses favorable physiochemical characteristics. The three-dimensional conformation underwent modeling and refinement, validated through in-silico methods. Additionally, a protein-protein molecular docking analysis was conducted to predict effective binding poses between the multi-epitope Vaccine and the Toll-like receptor 4 protein. The Molecular Dynamics (MD) investigation of the docked TLR4-vaccine complex demonstrated consistent stability over the simulation period, primarily attributed to electrostatic energy. The docked complex displayed minimal deformation and enhanced rigidity in the motion of residues during the dynamic simulation. Furthermore, codon translational optimization and computational cloning was performed to ensure the reliability and proper expression of the multi-Epitope Vaccine. It is crucial to emphasize that despite these computational validations, experimental research in the laboratory is imperative to demonstrate the immunogenicity and protective efficacy of the developed vaccine. This would involve practical assessments to ascertain the real-world effectiveness of the multi-epitope Vaccine.
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Affiliation(s)
- Sana Abdul Ghaffar
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan
| | - Haneen Tahir
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan
| | - Sher Muhammad
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan
| | - Muhammad Shahid
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan
| | - Tahir Naqqash
- Institute of Molecular Biology and Biotechnology, Bahauddin Zakariya University, Multan, Pakistan
| | | | - Thamer H. Albekairi
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Abdulrahman Alshammari
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Norah A. Albekairi
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Irfan Manzoor
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan
- Department of Biology, Indiana University, Bloomington, IN, United States
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Shahab M, Iqbal MW, Ahmad A, Alshabrmi FM, Wei DQ, Khan A, Zheng G. Immunoinformatics-driven In silico vaccine design for Nipah virus (NPV): Integrating machine learning and computational epitope prediction. Comput Biol Med 2024; 170:108056. [PMID: 38301512 DOI: 10.1016/j.compbiomed.2024.108056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 12/19/2023] [Accepted: 01/26/2024] [Indexed: 02/03/2024]
Abstract
The Nipah virus (NPV) is a highly lethal virus, known for its significant fatality rate. The virus initially originated in Malaysia in 1998 and later led to outbreaks in nearby countries such as Bangladesh, Singapore, and India. Currently, there are no specific vaccines available for this virus. The current work employed the reverse vaccinology method to conduct a comprehensive analysis of the entire proteome of the NPV virus. The aim was to identify and choose the most promising antigenic proteins that could serve as potential candidates for vaccine development. We have also designed B and T cell epitopes-based vaccine candidate using immunoinformatics approach. We have identified a total of 5 novel Cytotoxic T Lymphocytes (CTL), 5 Helper T Lymphocytes (HTL), and 6 linear B-cell potential antigenic epitopes which are novel and can be used for further vaccine development against Nipah virus. Then we performed the physicochemical properties, antigenic, immunogenic and allergenicity prediction of the designed vaccine candidate against NPV. Further, Computational analysis indicated that these epitopes possessed highly antigenic properties and were capable of interacting with immune receptors. The designed vaccine were then docked with the human immune receptors, namely TLR-2 and TLR-4 showed robust interaction with the immune receptor. Molecular dynamics simulations demonstrated robust binding and good dynamics. After numerous dosages at varied intervals, computational immune response modeling showed that the immunogenic construct might elicit a significant immune response. In conclusion, the immunogenic construct shows promise in providing protection against NPV, However, further experimental validation is required before moving to clinical trials.
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Affiliation(s)
- Muhammad Shahab
- State key Laboratories of Chemical Resources Engineering, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Muhammad Waleed Iqbal
- State key Laboratories of Chemical Resources Engineering, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Abbas Ahmad
- Department of Biotechnology Abdul Wali Khan University Mardan, Pakistan
| | - Fahad M Alshabrmi
- Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah, 51452, Saudi Arabia.
| | - Dong-Qing Wei
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China; Zhongjing Research and Industrialization Institute of Chinese Medicine, Zhongguancun Scientific Park, Meixi, Nayang, Henan, 473006, China; Peng Cheng Laboratory, Vanke Cloud City Phase I Building 8, Xili Street, Nashan District, Shenzhen, Guangdong, 518055, China
| | - Abbas Khan
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China; Zhongjing Research and Industrialization Institute of Chinese Medicine, Zhongguancun Scientific Park, Meixi, Nayang, Henan, 473006, China; Center for Microbiome Research, School of Medical and Life Sciences, Sunway University, Sunway City, Malaysia.
| | - Guojun Zheng
- State key Laboratories of Chemical Resources Engineering, Beijing University of Chemical Technology, Beijing, 100029, China.
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Naveed M, Ali U, Aziz T, Naveed R, Mahmood S, Khan MM, Alharbi M, Albekairi TH, Alasmari AF. An Aedes-Anopheles Vaccine Candidate Supplemented with BCG Epitopes Against the Aedes and Anopheles Genera to Overcome Hypersensitivity to Mosquito Bites. Acta Parasitol 2024; 69:483-504. [PMID: 38194049 DOI: 10.1007/s11686-023-00771-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 11/30/2023] [Indexed: 01/10/2024]
Abstract
BACKGROUND Skeeter syndrome is a severe local allergic response to mosquito bites that is accompanied by considerable inflammation and, in some cases, a systemic response like fever. People with the syndrome develop serious allergies, ranging from rashes to anaphylaxis or shock. The few available studies on mosquito venom immunotherapy have utilized whole-body preparations and small sample sizes. Still, owing to their little success, vaccination remains a promising alternative as well as a permanent solution for infections like Skeeter's. METHODS This study, therefore, illustrated the construction of an epitope-based vaccine candidate against Skeeter Syndrome using established immunoinformatic techniques. We selected three species of mosquitoes, Anopheles melas, Anopheles funestus, and Aedes aegypti, to derive salivary antigens usually found in mosquito bites. Our construct was also supplemented with bacterial epitopes known to elicit a strong TH1 response and suppress TH2 stimulation that is predicted to reduce hypersensitivity against the bites. RESULTS A quality factor of 98.9496, instability index of 38.55, aliphatic index of 79.42, solubility of 0.934747, and GRAVY score of -0.02 indicated the structural (tertiary and secondary) stability, thermostability, solubility, and hydrophilicity of the construct, respectively. The designed Aedes-Anopheles vaccine (AAV) candidate was predicted to be flexible and less prone to deformability with an eigenvalue of 1.5911e-9 and perfected the human immune response against Skeeter (hypersensitivity) and many mosquito-associated diseases as we noted the production of 30,000 Th1 cells per mm3 with little (insignificant production of Th2 cells. The designed vaccine also revealed stable interactions with the pattern recognition receptors of the host. The TLR2/vaccine complex interacted with a free energy of - 1069.2 kcal/mol with 26 interactions, whereas the NLRP3/vaccine complex interacted with a free energy of - 1081.2 kcal/mol with 16 molecular interactions. CONCLUSION Although being a pure in-silico study, the in-depth analysis performed herein speaks volumes of the potency of the designed vaccine candidate predicting that the proposition can withstand rigorous in-vitro and in-vivo clinical trials and may proceed to become the first preventative immunotherapy against mosquito bite allergy.
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Affiliation(s)
- Muhammad Naveed
- Department of Biotechnology, Faculty of Science and Technology, University of Central Punjab, Lahore, 54590, Punjab, Pakistan.
| | - Urooj Ali
- Department of Biotechnology, Quaid-I-Azam University Islamabad, Islamabad, 45320, Pakistan
| | - Tariq Aziz
- Department of Agriculture, University of Ioannina Arta, 47100, Arta, Greece.
| | - Rida Naveed
- Department of Biotechnology, Faculty of Science and Technology, University of Central Punjab, Lahore, 54590, Punjab, Pakistan
| | - Sarmad Mahmood
- Department of Biotechnology, Faculty of Science and Technology, University of Central Punjab, Lahore, 54590, Punjab, Pakistan
| | - Muhammad Mustajab Khan
- Department of Biotechnology, Quaid-I-Azam University Islamabad, Islamabad, 45320, Pakistan
| | - Metab Alharbi
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 2455, 11451, Riyadh, Saudi Arabia
| | - Thamer H Albekairi
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 2455, 11451, Riyadh, Saudi Arabia
| | - Abdullah F Alasmari
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 2455, 11451, Riyadh, Saudi Arabia
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Pritam M. Exploring the whole proteome of monkeypox virus to design B cell epitope-based oral vaccines using immunoinformatics approaches. Int J Biol Macromol 2023; 252:126498. [PMID: 37640189 DOI: 10.1016/j.ijbiomac.2023.126498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 08/05/2023] [Accepted: 08/22/2023] [Indexed: 08/31/2023]
Abstract
In the last few months 85,536 cases and 91 deaths were reported for monkeypox disease from 110 and 71 locations from all over the world, correspondingly. The vaccines of other viruses that belong to the Poxviridae family were recommended for monkeypox. There is no licensed vaccine available for monkeypox that originated from monkeypox virus. In the present study, using the reverse vaccinology approach we have performed whole proteome analysis of monkeypox virus to screen out the potential antigenic proteins that can be used as vaccine candidates. We have also designed 12 B cell epitopes-based vaccine candidates using immunoinformatics approach. We have found a total 15 potential antigenic proteins out of which 14 antigens are novel and can be used for further vaccine development against monkeypox. We have performed the physicochemical properties, antigenic, immunogenic and allergenicity prediction of the designed vaccine candidates MPOXVs (MPOXV1-MPOXV12). Further, we have performed molecular docking, in silico immune simulation and cloning of MPOXVs. All MPOXVs are potential vaccine candidate that can potentially activate the innate, cellular, and humoral immune response. However, further experimental validation is required before moving to clinical trials. This is the first oral vaccine reported for monkeypox virus derived from monkeypox proteins.
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Affiliation(s)
- Manisha Pritam
- Department of Biotechnology, AMITY University Lucknow Campus, India; National Institute of Allergy and Infectious Diseases (NIAID), NIH, MD, USA.
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Delgado KN, Montezuma-Rusca JM, Orbe IC, Caimano MJ, La Vake CJ, Luthra A, Hennelly CM, Nindo FN, Meyer JW, Jones LD, Parr JB, Salazar JC, Moody MA, Radolf JD, Hawley KL. Extracellular Loops of the Treponema pallidum FadL Orthologs TP0856 and TP0858 Elicit IgG Antibodies and IgG +-Specific B-Cells in the Rabbit Model of Experimental Syphilis. mBio 2022; 13:e0163922. [PMID: 35862766 PMCID: PMC9426418 DOI: 10.1128/mbio.01639-22] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 06/14/2022] [Indexed: 12/03/2022] Open
Abstract
The resurgence of syphilis in the new millennium has called attention to the importance of a vaccine for global containment strategies. Studies with immune rabbit serum (IRS) indicate that a syphilis vaccine should elicit antibodies (Abs) that promote opsonophagocytosis of treponemes by activated macrophages. The availability of three-dimensional models for Treponema pallidum's (Tp) repertoire of outer membrane proteins (OMPs) provides an architectural framework for identification of candidate vaccinogens with extracellular loops (ECLs) as the targets for protective Abs. Herein, we used Pyrococcus furiosus thioredoxin (PfTrx) as a scaffold to display Tp OMP ECLs to interrogate sera and peripheral blood mononuclear cells (PBMCs) from immune rabbits for ECL-specific Abs and B cells. We validated this approach using a PfTrx scaffold presenting ECL4 from BamA, a known opsonic target. Using scaffolds displaying ECLs of the FadL orthologs TP0856 and TP0858, we determined that ECL2 and ECL4 of both proteins are strongly antigenic. Comparison of ELISA and immunoblot results suggested that the PfTrx scaffolds present conformational and linear epitopes. We then used the FadL ECL2 and ECL4 PfTrx constructs as "hooks" to confirm the presence of ECL-specific B cells in PBMCs from immune rabbits. Our results pinpoint immunogenic ECLs of two newly discovered OMPs, while advancing the utility of the rabbit model for circumventing bottlenecks in vaccine development associated with large-scale production of folded OMPs. They also lay the groundwork for production of rabbit monoclonal Abs (MAbs) to characterize potentially protective ECL epitopes at the atomic level. IMPORTANCE Recent identification and structural modeling of Treponema pallidum's (Tp) repertoire of outer membrane proteins (OMPs) represent a critical breakthrough in the decades long quest for a syphilis vaccine. However, little is known about the antigenic nature of these β-barrel-forming OMPs and, more specifically, their surface exposed regions, the extracellular loops (ECLs). In this study, using Pyrococcus furiosus thioredoxin (PfTrx) as a scaffold to display Tp OMP ECLs, we interrogated immune rabbit sera and peripheral blood mononuclear cells for the presence of antibodies (Abs) and circulating rare antigen-specific B cells. Our results pinpoint immunogenic ECLs of two newly discovered OMPs, while advancing the utility of the rabbit model for surveying the entire Tp OMPeome for promising OMP vaccinogens. This work represents a major advancement toward characterizing potentially protective OMP ECLs and future vaccine studies. Additionally, this strategy could be applied to OMPs of nonspirochetal bacterial pathogens.
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Affiliation(s)
| | - Jairo M Montezuma-Rusca
- Department of Medicine, UConn Health, Farmington, Connecticut, USA
- Division of Infectious Diseases, UConn Health, Farmington, Connecticut, USA
- Department of Pediatrics, UConn Health, Farmington, Connecticut, USA
| | - Isabel C Orbe
- Department of Pediatrics, UConn Health, Farmington, Connecticut, USA
| | - Melissa J Caimano
- Department of Medicine, UConn Health, Farmington, Connecticut, USA
- Department of Pediatrics, UConn Health, Farmington, Connecticut, USA
- Department of Molecular Biology and Biophysics, UConn Health, Farmington, Connecticut, USA
| | - Carson J La Vake
- Department of Pediatrics, UConn Health, Farmington, Connecticut, USA
| | - Amit Luthra
- Department of Medicine, UConn Health, Farmington, Connecticut, USA
- Department of Molecular Biology and Biophysics, UConn Health, Farmington, Connecticut, USA
| | - Christopher M Hennelly
- Division of Infectious Diseases, Department of Medicine, and Institute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Fredrick N Nindo
- Division of Infectious Diseases, Department of Medicine, and Institute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Jacob W Meyer
- Duke Human Vaccine Institute, Durham, North Carolina, USA
| | | | - Jonathan B Parr
- Division of Infectious Diseases, Department of Medicine, and Institute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Juan C Salazar
- Department of Pediatrics, UConn Health, Farmington, Connecticut, USA
- Division of Infectious Diseases and Immunology, Connecticut Children's, Hartford, Connecticut, USA
- Department of Immunology, UConn Health, Farmington, Connecticut, USA
| | - M Anthony Moody
- Duke Human Vaccine Institute, Durham, North Carolina, USA
- Department of Pediatrics, Duke University Medical Center, Durham, North Carolina, USA
- Department of Immunology, Duke University Medical Center, Durham, North Carolina, USA
| | - Justin D Radolf
- Department of Medicine, UConn Health, Farmington, Connecticut, USA
- Department of Pediatrics, UConn Health, Farmington, Connecticut, USA
- Department of Molecular Biology and Biophysics, UConn Health, Farmington, Connecticut, USA
- Department of Immunology, UConn Health, Farmington, Connecticut, USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, Connecticut, USA
| | - Kelly L Hawley
- Department of Medicine, UConn Health, Farmington, Connecticut, USA
- Department of Pediatrics, UConn Health, Farmington, Connecticut, USA
- Division of Infectious Diseases and Immunology, Connecticut Children's, Hartford, Connecticut, USA
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Vaccinomics to Design a Multi-Epitopes Vaccine for Acinetobacter baumannii. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19095568. [PMID: 35564967 PMCID: PMC9104312 DOI: 10.3390/ijerph19095568] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 04/23/2022] [Accepted: 04/28/2022] [Indexed: 12/13/2022]
Abstract
Antibiotic resistance (AR) is the result of microbes’ natural evolution to withstand the action of antibiotics used against them. AR is rising to a high level across the globe, and novel resistant strains are emerging and spreading very fast. Acinetobacter baumannii is a multidrug resistant Gram-negative bacteria, responsible for causing severe nosocomial infections that are treated with several broad spectrum antibiotics: carbapenems, β-lactam, aminoglycosides, tetracycline, gentamicin, impanel, piperacillin, and amikacin. The A. baumannii genome is superplastic to acquire new resistant mechanisms and, as there is no vaccine in the development process for this pathogen, the situation is more worrisome. This study was conducted to identify protective antigens from the core genome of the pathogen. Genomic data of fully sequenced strains of A. baumannii were retrieved from the national center for biotechnological information (NCBI) database and subjected to various genomics, immunoinformatics, proteomics, and biophysical analyses to identify potential vaccine antigens against A. baumannii. By doing so, four outer membrane proteins were prioritized: TonB-dependent siderphore receptor, OmpA family protein, type IV pilus biogenesis stability protein, and OprD family outer membrane porin. Immuoinformatics predicted B-cell and T-cell epitopes from all four proteins. The antigenic epitopes were linked to design a multi-epitopes vaccine construct using GPGPG linkers and adjuvant cholera toxin B subunit to boost the immune responses. A 3D model of the vaccine construct was built, loop refined, and considered for extensive error examination. Disulfide engineering was performed for the stability of the vaccine construct. Blind docking of the vaccine was conducted with host MHC-I, MHC-II, and toll-like receptors 4 (TLR-4) molecules. Molecular dynamic simulation was carried out to understand the vaccine-receptors dynamics and binding stability, as well as to evaluate the presentation of epitopes to the host immune system. Binding energies estimation was achieved to understand intermolecular interaction energies and validate docking and simulation studies. The results suggested that the designed vaccine construct has high potential to induce protective host immune responses and can be a good vaccine candidate for experimental in vivo and in vitro studies.
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Keshavarzi Arshadi A, Webb J, Salem M, Cruz E, Calad-Thomson S, Ghadirian N, Collins J, Diez-Cecilia E, Kelly B, Goodarzi H, Yuan JS. Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development. Front Artif Intell 2020; 3:65. [PMID: 33733182 PMCID: PMC7861281 DOI: 10.3389/frai.2020.00065] [Citation(s) in RCA: 97] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 07/17/2020] [Indexed: 12/31/2022] Open
Abstract
SARS-COV-2 has roused the scientific community with a call to action to combat the growing pandemic. At the time of this writing, there are as yet no novel antiviral agents or approved vaccines available for deployment as a frontline defense. Understanding the pathobiology of COVID-19 could aid scientists in their discovery of potent antivirals by elucidating unexplored viral pathways. One method for accomplishing this is the leveraging of computational methods to discover new candidate drugs and vaccines in silico. In the last decade, machine learning-based models, trained on specific biomolecules, have offered inexpensive and rapid implementation methods for the discovery of effective viral therapies. Given a target biomolecule, these models are capable of predicting inhibitor candidates in a structural-based manner. If enough data are presented to a model, it can aid the search for a drug or vaccine candidate by identifying patterns within the data. In this review, we focus on the recent advances of COVID-19 drug and vaccine development using artificial intelligence and the potential of intelligent training for the discovery of COVID-19 therapeutics. To facilitate applications of deep learning for SARS-COV-2, we highlight multiple molecular targets of COVID-19, inhibition of which may increase patient survival. Moreover, we present CoronaDB-AI, a dataset of compounds, peptides, and epitopes discovered either in silico or in vitro that can be potentially used for training models in order to extract COVID-19 treatment. The information and datasets provided in this review can be used to train deep learning-based models and accelerate the discovery of effective viral therapies.
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Affiliation(s)
- Arash Keshavarzi Arshadi
- Burnett School of Biomedical Sciences, University of Central Florida, Orlando, FL, United States
| | - Julia Webb
- Burnett School of Biomedical Sciences, University of Central Florida, Orlando, FL, United States
| | - Milad Salem
- Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, United States
| | | | | | - Niloofar Ghadirian
- Department of Chemistry and Biochemistry, University of Arizona, Tucson, AZ, United States
| | - Jennifer Collins
- Burnett School of Biomedical Sciences, University of Central Florida, Orlando, FL, United States
| | | | | | - Hani Goodarzi
- Department of Biochemistry and Biophysics, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, United States
| | - Jiann Shiun Yuan
- Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, United States
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Li H, Schaduangrat N, Simeon S, Nantasenamat C. Computational study on the origin of the cancer immunotherapeutic potential of B and T cell epitope peptides. MOLECULAR BIOSYSTEMS 2018; 13:2310-2322. [PMID: 28880325 DOI: 10.1039/c7mb00219j] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Immune therapy is generally seen as the future of cancer treatment. The discovery of tumor-associated antigens and cytotoxic T lymphocyte epitope peptides spurned intensive research into effective peptide-based cancer vaccines. One of the major obstacles hindering the development of peptide-based cancer vaccines is the lack of humoral response induction. As of now, very limited work has been performed to identify epitope peptides capable of inducing both cellular and humoral anticancer responses. In addition, no research has been carried out to analyze the structure and properties of peptides responsible for such immunological activities. This study utilizes a machine learning method together with interpretable descriptors in an attempt to identify parameters determining the immunotherapeutic activity of cancer epitope peptides.
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Affiliation(s)
- Hao Li
- Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand.
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Abdulrahman A, Ghanem A. Recent advances in chromatographic purification of plasmid DNA for gene therapy and DNA vaccines: A review. Anal Chim Acta 2018; 1025:41-57. [PMID: 29801607 DOI: 10.1016/j.aca.2018.04.001] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 04/03/2018] [Accepted: 04/05/2018] [Indexed: 12/16/2022]
Abstract
The wide spread of infectious diseases have provoked the scientists to develop new types of vaccines. Among the different types of vaccines, the recently discovered plasmid DNA vaccines, have gained tremendous attentions in the last few decades as a modern approach of vaccination. The scientific interest in plasmid DNA vaccines is attributed to their prominent efficacy as they trigger not only the cellular immune response but also the humoral immune responses. Moreover, pDNA vaccines are easily to be stored, shipped and produced. However, the purification of the pDNA vaccines is a crucial step in their production and administration, which is usually conducted by different chromatographic techniques. This review summarizes the most recent chromatographic purification methods provided in the literature during the last five years following our last review in 2013, including affinity chromatography, hydrophobic interaction chromatography, ion exchange chromatography, multimodal chromatography, sample displacement chromatography and miscellaneous chromatographic methods.
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Affiliation(s)
- Ahmed Abdulrahman
- Chirality Program, Faculty of Science and Technology, University of Canberra, Australian Capital Territory (ACT), 2617, Australia
| | - Ashraf Ghanem
- Chirality Program, Faculty of Science and Technology, University of Canberra, Australian Capital Territory (ACT), 2617, Australia. http://www.chiralitygroup.com
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Asad Y, Ahmad S, Rungrotmongkol T, Ranaghan KE, Azam SS. Immuno-informatics driven proteome-wide investigation revealed novel peptide-based vaccine targets against emerging multiple drug resistant Providencia stuartii. J Mol Graph Model 2018; 80:238-250. [PMID: 29414043 DOI: 10.1016/j.jmgm.2018.01.010] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Revised: 12/22/2017] [Accepted: 01/15/2018] [Indexed: 11/22/2022]
Abstract
The bacterium Providencia stuartii, is associated with urinary tract infections and is the most common cause of purple urine bag syndrome. The increasing multi-drug resistance pattern shown by the pathogen and lack of licensed vaccines make treatment of infections caused by P. stuartii challenging. As vaccinology data against the pathogen is scarce, an in silico proteome based Reverse Vaccinology (RV) protocol, in combination with subtractive proteomics is introduced in this work to screen potential vaccine candidates against P. stuartii. The analysis identified three potential vaccine candidates for designing broad-spectrum and strain-specific peptide vaccines: FimD4, FimD6, and FimD8. These proteins are essential for pathogen survival, localized in the outer membrane, virulent, and antigenic in nature. Immunoproteomic tools mapped surface exposed and non-allergenic 9mer B-cell derived T-cell antigenic epitopes for the proteins. The epitopes also show stable and rich interactions with the most predominant HLA allele (DRB1*0101) in the human population. Metabolic pathway annotation of the proteins indicated that fimbrial biogenesis outer membrane usher protein (FimD6) is the most suitable candidate for vaccine design, due to its involvement in several significant pathways. These pathways include: the bacterial secretion system, two-component system, β-lactam resistance, and cationic antimicrobial peptide pathways. The predicted epitopes may provide a basis for designing a peptide-based vaccine against P. stuartii.
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Affiliation(s)
- Yelda Asad
- Computational Biology Lab, National Center for Bioinformatics, Quaid-i-Azam University, Islamabad, Pakistan
| | - Sajjad Ahmad
- Computational Biology Lab, National Center for Bioinformatics, Quaid-i-Azam University, Islamabad, Pakistan
| | - Thanyada Rungrotmongkol
- Biocatalyst and Environmental Biotechnology Research unit, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand; Ph.D. Program in Bioinformatics and Computational Biology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Kara E Ranaghan
- Centre for Computational Chemistry, University of Bristol, Bristol, United Kingdom
| | - Syed Sikander Azam
- Computational Biology Lab, National Center for Bioinformatics, Quaid-i-Azam University, Islamabad, Pakistan; Biocatalyst and Environmental Biotechnology Research unit, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.
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Hegde NR, Gauthami S, Sampath Kumar HM, Bayry J. The use of databases, data mining and immunoinformatics in vaccinology: where are we? Expert Opin Drug Discov 2017; 13:117-130. [PMID: 29226722 DOI: 10.1080/17460441.2018.1413088] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
INTRODUCTION Vaccinology has evolved from a sub-discipline focussed on simplistic vaccine development based on antibody-mediated protection to a separate discipline involving epidemiology, host and pathogen biology, immunology, genomics, proteomics, structure biology, protein engineering, chemical biology, and delivery systems. Data mining in combination with bioinformatics has provided a scaffold linking all these disciplines to the design of vaccines and vaccine adjuvants. Areas covered: This review provides background knowledge on immunological aspects which have been exploited with informatics for the in silico analysis of immune responses and the design of vaccine antigens. Furthermore, the article presents various databases and bioinformatics tools, and discusses B and T cell epitope predictions, antigen design, adjuvant research and systems immunology, highlighting some important examples, and challenges for the future. Expert opinion: Informatics and data mining have not only reduced the time required for experimental immunology, but also contributed to the identification and design of novel vaccine candidates and the determination of biomarkers and pathways of vaccine response. However, more experimental data is required for benchmarking immunoinformatic tools. Nevertheless, developments in immunoinformatics and reverse vaccinology, which are nascent fields, are likely to hasten vaccine discovery, although the path to regulatory approval is likely to remain a necessary impediment.
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Affiliation(s)
| | - S Gauthami
- b Ella Foundation, Turkapally , Hyderabad , India
| | - H M Sampath Kumar
- c Council of Scientific and Industrial Research - Indian Institute of Chemical Technology , Hyderabad , India
| | - Jagadeesh Bayry
- d Institut National de la Santé et de la Recherche Médicale (INSERM) Unité 1138 , Centre de Recherche des Cordeliers, Paris , France
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